As the number of users viewing information and purchasing items electronically increases, there is a corresponding increase in the amount of advertising revenue spent in electronic environments. In some cases, advertisements are specifically selected for certain pages or other interfaces displayed to a user. In other cases, these advertisements are selected based on content that can be displayed in any of a number of different pages. For example, a user might search for information about a keyword through a search engine. When a results page is returned to the user that includes search results relating to that keyword, at least one advertisement can be included with the results page that relates to the keyword and/or search results. Often, the advertisement includes a hypertext link or other user-selectable element that enables the user to navigate to another page or display relating to the advertisement.
In many cases, there can be multiple advertisements or offers displayed that are related to content of a given page displayed to a user. For example, a user viewing a search results page might see advertisements for items that are related to at least one keyword that was used for the search query. In another example, a user viewing a display page for an item in an electronic marketplace might see one or more offers or advertisements for items that are related to some aspect of the featured item on that display page. In order to determine which advertisements are to be displayed in each case, as well as the order in which those advertisements appear, a provider of a site or other such electronic content can utilize a “bidding” process wherein potential advertisers or sponsors submit bids indicating how much an advertiser is willing to spend for a sponsored ad to be displayed on the page. Winning bids then can be ranked to not only determine which ads to display, but the bids can be ranked from highest to lowest in order to determine the order in which the ads are displayed.
Due to the large number of combinations of items, keywords, advertisements, and other such aspects, many advertisers and providers rely on automated advertising systems to generate, accept, rank, and otherwise process such bids. It thus can be important to an advertiser that such a system generate reasonable bids, and that the generated bids meet business targets for that advertiser. For example, an advertiser might utilize an efficiency target, where efficiency is determined as the amount of money spent for an advertisement, or the “spend” for that ad, compared to the corresponding amount of revenue generated as a result of the advertising. An advertiser then might adjust all advertising bids by a certain percent in order to improve the advertising efficiency. In some cases, an advertiser might also manually adjust a bid price for a certain item or category of items in order to improve the efficiency in those areas.
As search engines continue to advance, however, the determination of which advertisements to feature becomes more complex. For example, a search engine might utilize a “quality score” for an advertiser in conjunction with the bid prices from the advertiser. In this case, an advertiser might not be featured in the top spot even if that advertiser has the highest bid for an item when the advertiser has a relatively low quality score. Another advancement is that search engines can use broad matching algorithms, where search engines may decide to enter keywords, specified by an advertiser, into broader and broader auctions in order to increase potential revenue from the single keyword as the bid prices increase. Further, many systems utilize various rollup levels such that the efficiency for a given keyword can be forecast using data for other keywords that should perform similarly. Using such a bidding approach, however, can be a “pessimistic” approach as the approach does not consider the actual cost of the rollup keywords, which could result in a bid that is potentially too low and that could prevent this new keyword from ever showing and gathering data necessary to make an accurate bid determination.